Prediction of the Standard Deviation of Wind Speed Turbulence

2018 ◽  
Author(s):  
G. R. Ren ◽  
◽  
J. F. Liu ◽  
J. Wan ◽  
Q. H. Hu ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Wind Speed

scholarly journals The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality

2019 ◽  
Vol 4 (2) ◽  
pp. 343-353 ◽  
Author(s):  
Tyler C. McCandless ◽  
Sue Ellen Haupt
Keyword(s):  
Machine Learning ◽  
Standard Deviation ◽  
Wind Speed ◽  
Wind Power ◽  
Power Conversion ◽  
Jensen’S Inequality ◽  
Jensen's Inequality ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Abstract. Wind power is a variable generation resource and therefore requires accurate forecasts to enable integration into the electric grid. Generally, the wind speed is forecast for a wind plant and the forecasted wind speed is converted to power to provide an estimate of the expected generating capacity of the plant. The average wind speed forecast for the plant is a function of the underlying meteorological phenomena being predicted; however, the wind speed for each turbine at the farm is also a function of the local terrain and the array orientation. Conversion algorithms that assume an average wind speed for the plant, i.e., the super-turbine power conversion, assume that the effects of the local terrain and array orientation are insignificant in producing variability in the wind speeds across the turbines at the farm. Here, we quantify the differences in converting wind speed to power at the turbine level compared with a super-turbine power conversion for a hypothetical wind farm of 100 2 MW turbines as well as from empirical data. The simulations with simulated turbines show a maximum difference of approximately 3 % at 11 m s−1 with a 1 m s−1 standard deviation of wind speeds and 8 % at 11 m s−1 with a 2 m s−1 standard deviation of wind speeds as a consequence of Jensen's inequality. The empirical analysis shows similar results with mean differences between converted wind speed to power and measured power of approximately 68 kW per 2 MW turbine. However, using a random forest machine learning method to convert to power reduces the error in the wind speed to power conversion when given the predictors that quantify the differences due to Jensen's inequality. These significant differences can lead to wind power forecasters overestimating the wind generation when utilizing a super-turbine power conversion for high wind speeds, and indicate that power conversion is more accurately done at the turbine level if no other compensatory mechanism is used to account for Jensen's inequality.

scholarly journals Comparison Of Three Numerical Methods For Estimating Weibull Parameters Using Weibull Distribution Model In Nigeria

2020 ◽  
Vol 27 (2) ◽  
pp. 8-15
Author(s):  
J.A. Oyewole ◽  
F.O. Aweda ◽  
D. Oni
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Probability Density Function ◽  
Weibull Distribution ◽  
Probability Density ◽  
Density Function ◽  
Accurate Estimation ◽  
Weibull Parameters ◽  
Factor Method ◽  
Deviation Method

There is a crucial need in Nigeria to enhance the development of wind technology in order to boost our energy supply. Adequate knowledge about the wind speed distribution becomes very essential in the establishment of Wind Energy Conversion Systems (WECS). Weibull Probability Density Function (PDF) with two parameters is widely accepted and is commonly used for modelling, characterizing and predicting wind resource and wind power, as well as assessing optimum performance of WECS. Therefore, it is paramount to precisely estimate the scale and shape parameters for all regions or sites of interest. Here, wind data from year 2000 to 2010 for four different locations (Port Harcourt, Ikeja, Kano and Jos) were analysed and the Weibull parameters was determined. The three methods employed are Mean Standard Deviation Method (MSDM), Energy Pattern Factor Method (EPFM) and Method of Moments (MOM) for estimating Weibull parameters. The method that gave the most accurate estimation of the wind speed was MSDM method, while Energy Pattern Factor Method (EPFM) is the most reliable and consistent method for estimating probability density function of wind. Keywords: Weibull Distribution, Method of Moment, Mean Standard Deviation Method, Energy Pattern Method

scholarly journals Unmanned Surface Vehicle (USV) performance test in Bintan Island Waters

2021 ◽  
Vol 944 (1) ◽  
pp. 012013
Author(s):  
R Fauzi ◽  
I Jaya ◽  
M Iqbal
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Water Surface ◽  
Performance Test ◽  
Average Frequency ◽  
Underwater Imaging ◽  
Unmanned Surface Vehicle ◽  
Unmanned Surface Vehicles ◽  
Vehicle Acceleration ◽  
Direction Of Movement

Abstract An unmanned surface vehicle (USV) is an unmanned vehicle that is operated on the surface of the water for certain purposes, for example, bathymetry measurement, underwater imaging, etc. These unmanned surface vehicles can be used in impassable waters for crewed vessels in dangerous waters. This research measures the movement of the vehicle acceleration and then calculates it as the USV roll and pitch values. The direction of movement and wind speed and the height of the water surface at low tide are also aspects measured in this research. An accelerometer is a sensor that can measure the acceleration of an object, both dynamic and static. Based on the observations, the highest roll value is 6.0° deep while the highest pitch value is 6.5°. The standard deviation value at roll conditions of 2.92 and the standard deviation value at pitch conditions of 1.25. The average frequency of roll conditions is 2.18 and pitch conditions of 1.13. The dominant wind moves from the south to the southwest with a dominant speed ranging from 3.0 to 4.0 m/s. The results of this research indicate that the USV has a good performance so that it is possible to collect data in the water.

Statistical analysis of wind resource and energy potential assessment of Quaidabad site, Sindh Pakistan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zahid Hussain Hulio ◽  
Gm Yousufzai ◽  
Wei Jiang
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Energy Density ◽  
Wind Shear ◽  
Economic Assessment ◽  
Energy Potential ◽  
Content Type ◽  
Mean Values ◽  
The Mean ◽  
Wind Resource

Purpose Pakistan is an energy starving country that needs continuous supply of energy to keep up its economic speed. The aim of this paper is to assess the wind resource and energy potential of Quaidabad site for minimizing the dependence on fuels and improving the environment. Design/methodology/approach The Quaidabad site wind shear coefficient and turbulence intensity factor are investigated. The two-parameter k and c Weibull distribution function is used to analyze the wind speed of site. The standard deviation of the site is also assessed for a period of a year. The wind power density and energy density are assessed for a period of a year. The economic assessment of energy/kWh is investigated for selection of appropriate wind turbine. Findings The mean wind shear coefficient was observed to be 0.2719, 0.2191 and 0.1698 at 20, 40 and 60 m, respectively, for a period of a year. The mean wind speed is found to be 2.961, 3.563, 3.907 and 4.099 m/s at 20, 40, 60 and 80 m, respectively. The mean values of k parameters were observed to be 1.563, 2.092, 2.434 and 2.576 at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean values of c m/s parameter were found to be 3.341, 4.020, 4.408 and 4.625 m/s at 20, 40, 60 and 80 m, respectively, for a period of a year. The major portion of values of standard deviation was found to be in between 0.1 and 2.00 at 20, 40, 60 and 80 m. The wind power density (W/m2) sum total values were observed to be 351, 597, 792 and 923 W/m2 at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean coefficient of variation was found to be 0.161, 0.130, 0.115 and 0.105 at 20, 40, 60 and 80 m, respectively. The sum total energy density was observed to be 1,157, 2,156, 2,970 and 3,778 kWh/m2 at 20, 40, 60 and 80 m, respectively. The economic assessment is showing that wind turbine E has the minimum cost US$0.049/kWh. Originality/value The Quaidabad site is suitable for installing the utility wind turbines for energy generation at the lowest cost.

scholarly journals The Influence of Boundary Layer Processes on the Diurnal Variation of the Climatological Near-Surface Wind Speed Probability Distribution over Land*

2012 ◽  
Vol 25 (18) ◽  
pp. 6441-6458 ◽  
Author(s):  
Yanping He ◽  
Norman A. McFarlane ◽  
Adam H. Monahan
Keyword(s):  
Boundary Layer ◽  
Standard Deviation ◽  
Wind Speed ◽  
Probability Distribution ◽  
Wind Power ◽  
Land Surface ◽  
Vertical Structure ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface

Abstract Knowledge of the diurnally varying land surface wind speed probability distribution is essential for surface flux estimation and wind power management. Global observations indicate that the surface wind speed probability density function (PDF) is characterized by a Weibull-like PDF during the day and a nighttime PDF with considerably greater skewness. Consideration of long-term tower observations at Cabauw, the Netherlands, indicates that this nighttime skewness is a shallow feature connected to the formation of a stably stratified nocturnal boundary layer. The observed diurnally varying vertical structure of the leading three climatological moments of near-surface wind speed (mean, standard deviation, and skewness) and the wind power density at the Cabauw site can be successfully simulated using the single-column version of the Canadian Centre for Climate Modelling and Analysis (CCCma) fourth-generation atmospheric general circulation model (CanAM4) with a new semiempirical diagnostic turbulent kinetic energy (TKE) scheme representing downgradient turbulent transfer processes for cloud-free conditions. This model also includes a simple stochastic representation of intermittent turbulence at the boundary layer inversion. It is found that the mean and the standard deviation of wind speed are most influenced by large-scale “weather” variability, while the shape of the PDF is influenced by the intermittent mixing process. This effect is quantitatively dependent on the asymptotic flux Richardson number, which determines the Prandtl number in stable flows. High vertical resolution near the land surface is also necessary for realistic simulation of the observed fine vertical structure of wind speed distribution.

scholarly journals Model-Based Projections and Uncertainties of Near-Surface Wind Climate in Western Canada

2016 ◽  
Vol 55 (10) ◽  
pp. 2229-2245 ◽  
Author(s):  
Jeffrey T. Daines ◽  
Adam H. Monahan ◽  
Charles L. Curry
Keyword(s):  
Power Generation ◽  
Standard Deviation ◽  
Wind Speed ◽  
Wind Power ◽  
Surface Wind ◽  
Western Canada ◽  
Near Surface ◽  
Wind Speeds ◽  
Ensemble Mean ◽  
Wind Climate

AbstractNear-surface wind is important in forestry, agriculture, air pollution, building energy use, and wind power generation. In western Canada it presently plays a minor role in power generation, but ongoing reductions in the cost of wind power infrastructure and the increasing costs of conventional power generation (including environmental costs) motivate the assessment of the projected future wind climate and uncertainties in this projection. Multiple realizations of the Canadian Regional Climate Model (CRCM) at 45-km resolution were driven by two global climate models over the periods 1971–2000 (using historical greenhouse gas concentrations) and 2031–60 (using the SRES-A2 concentration scenario). Hourly wind speeds from 30 stations were analyzed over 1971–2000 and used to calibrate downscaled ensembles of projected wind speed distributions over 2031–60. At most station locations modest increases in mean wind speed were found for a majority of the projections, but with an ensemble spread of the same order of magnitude as the increases. Relative changes in mean wind speeds at station locations were found to be insensitive to the station observations and calibration technique. In view of this result, projected relative changes in future wind climate over the entire CRCM domain were estimated using uncalibrated pairs of past-period and future-period wind speed distributions. The relative changes are robust, in the sense that their ensemble mean relative change is greater than their standard deviation, but are not very substantial, in the sense that their ensemble mean change is generally less than the standard deviation of their annual means.

scholarly journals Characterization of the Martian Convective Boundary Layer

2009 ◽  
Vol 66 (7) ◽  
pp. 2044-2058 ◽  
Author(s):  
Germán Martínez ◽  
Francisco Valero ◽  
Luis Vázquez
Keyword(s):  
Boundary Layer ◽  
Surface Layer ◽  
Standard Deviation ◽  
Wind Speed ◽  
Viscous Dissipation ◽  
Mixed Layer ◽  
Dissipation Rate ◽  
Horizontal Wind

Abstract The authors have carried out an extensive characterization of the Martian mixed layer formed under convective conditions. The values of the mixed layer height, convective velocity scale, convective temperature scale, mean temperature standard deviation, mean horizontal and vertical velocity standard deviations, and mean turbulent viscous dissipation rate have been obtained during the strongest convective hours for the mixed layer. In addition, the existing database of the surface layer has been improved by recalculating some parameters (e.g., Monin–Obukhov length, friction velocity, or scale temperature) that had already been obtained in previous papers by other means and also by calculating new ones, such as the standard deviation of the vertical wind speed velocity, the turbulent viscous dissipation rate, and eddy transfer coefficients for momentum and heat. The Earth counterparts of all these magnitudes are also shown. In this paper, a comprehensive database concerning the whole convective planetary boundary layer on Mars is displayed, and a detailed terrestrial comparison is established. The inputs of this work are hourly in situ temperature, hourly in situ horizontal wind speed, and hourly simulated ground temperature for specific selected Sols of the Viking and Pathfinder landers. These data correspond to typical low and midlatitude northern summertime conditions, with weak prevailing winds. To handle this set of data, surface layer and mixed layer similarity theory have been used at the strongest convective hours. In addition, the inclusion of a parameterization of a molecular sublayer and prescribed values of the surface roughness has been considered.

scholarly journals Evaluation of Three-Beam and Four-Beam Profiler Wind Measurement Techniques Using a Five-Beam Wind Profiler and Collocated Meteorological Tower

2005 ◽  
Vol 22 (8) ◽  
pp. 1167-1180 ◽  
Author(s):  
Ahoro Adachi ◽  
Takahisa Kobayashi ◽  
Kenneth S. Gage ◽  
David A. Carter ◽  
Leslie M. Hartten ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Measurement Techniques ◽  
Doppler Velocity ◽  
Small Scale ◽  
Wind Profiler ◽  
Meteorological Tower ◽  
Beam Method ◽  
Vertical Beam ◽  
Beam Technique

Abstract In this paper a five-beam wind profiler and a collocated meteorological tower are used to estimate the accuracy of four-beam and three-beam wind profiler techniques in measuring horizontal components of the wind. In the traditional three-beam technique, the horizontal components of wind are derived from two orthogonal oblique beams and the vertical beam. In the less used four-beam method, the horizontal winds are found from the radial velocities measured with two orthogonal sets of opposing coplanar beams. In this paper the observations derived from the two wind profiler techniques are compared with the tower measurements using data averaged over 30 min. Results show that, while the winds measured using both methods are in overall agreement with the tower measurements, some of the horizontal components of the three-beam-derived winds are clearly spurious when compared with the tower-measured winds or the winds derived from the four oblique beams. These outliers are partially responsible for a larger 30-min, three-beam standard deviation of the profiler/tower wind speed differences (2.2 m s−1), as opposed to that from the four-beam method (1.2 m s−1). It was also found that many of these outliers were associated with periods of transition between clear air and rain, suggesting that the three-beam technique is more sensitive to small-scale variability in the vertical Doppler velocity because of its reliance on the point measurement from the vertical beam, while the four-beam method is surprisingly robust. Even after the removal of the rain data, the standard deviation of the wind speed error from the three-beam method (1.5 m s−1) is still much larger than that from the four-beam method. Taken together, these results suggest that the spatial variability of the vertical airflow in nonrainy periods or hydrometeor fall velocities in rainy periods makes the vertical beam velocities significantly less representative over the area across the three beams, and decreases the precision of the three-beam method. It is concluded that profilers utilizing the four-beam wind profiler technique have better reliability than wind profilers that rely on the three-beam wind profiler technique.

scholarly journals Horizontal and vertical distribution of wind speed in a vegetation canopy.

1991 ◽  
Vol 39 (3) ◽  
pp. 165-178
Author(s):  
A.F.G. Jacobs ◽  
J.H. van Boxel
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Mean Value ◽  
Night Time ◽  
Scaling Parameter ◽  
Atmospheric Stratification ◽  
Scaling Parameters ◽  
Mean Wind Speed ◽  
Applied Meteorology ◽  
The Mean

Wind speed measurements within a maize row canopy were carried out to investigate the horizontal and vertical variability of the mean wind speed and its standard deviation. Attention was given to finding adequate scaling parameters of the within-canopy wind speed profiles under various atmospheric stratification states. A validation of existing model simulations was also carried out. The horizontal mean wind speed and its standard deviation can vary about 20% from its spatial mean value. During day time and night time the friction velocity appears to be a good scaling parameter. Clear nights, however, are exceptions, when the wind speed above the crop drops to a very low value. Then the free convection velocity appears to be an appropriate scaling parameter for the within-canopy processes. The canopy models of Wilson & Shaw [Journal of Applied Meteorology (1977) 16, 1197-1205] and Li et al. [Boundary-Layer Meteorology (1985) 33, 77-84] were found to simulate the spatially averaged mean wind profile within the range of the horizontal variability. (Abstract retrieved from CAB Abstracts by CABI’s permission)

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